Aspects of the present invention relate generally to electrical junctions arranged between electrical conductors.
Further aspects relate to electrical devices comprising electrical junctions and neural networks comprising electrical junctions.
Neural networks are widely used in pattern recognition and classification, with many potential applications. The parameters (e.g., ‘synaptic weights’) of the neural network may be adaptively trained on a set of patterns during a learning process, following which the neural network is able to recognize or classify patterns of the same kind.
Neural network applications may include pattern recognition, classification, and identification of fingerprints, faces, voiceprints, similar portions of text, similar strings of genetic code, prediction of the behavior of systems etc.
Hardware implementations of neural network architectures require a multitude of interconnects to connect all outputs of neurons from one layer to the inputs of neurons from the next layer. The number of such connections may be very large in preferred systems. Their physical implementation is challenging because current hardware fabrication relies mostly on 2D fabrication techniques. However, with such 2D fabrication techniques the signal lines cannot be crossed without creating a shortcut. Also multi-layer CMOS implementations with several metal layers have limited capabilities to solve this issue.
Accordingly, it is generally desirable to provide other electrical junctions, in particular electrical junctions that facilitate an integration of crossings between electrical wires with high density.